The present invention relates to diversity reception of signals propagating over distinct fading channels.
It is known to combine a diversity system with an equalization system for purposes of improving the performance of a receiver. One such technique is the decision feedback equalization in which matched filters or forward equalizers are provided respectively at diversity antennas and their outputs are combined and fed into a decision-feedback equalizer (as described in K. Watanabe, "Adaptive Matched Filter And Its Significance To Anti-Multipath Fading", IEEE publication (CH2314-3/86/0000-1455) 1986, pages 1455 to 1459, and P. Monsen, "Adaptive Equalization of The Slow Fading Channel", IEEE, Transactions of Communications, Vol. COM-22, No. 8, August 1974).
Another technique is the maximum likelihood estimation in which the quality (spread of intersymbol interference and signal to noise ratio) of a received signal at each diversity antenna is estimated and a signal having the largest value is selected on the basis of the quality estimates (as described in Okanoue, Furuya, "A New Post-Detection Selection Diversity With MLSE Equalization", B-502, Institutes of Electronics Information and Communications, Autumn National Meeting, 1989). To implement the maximum likelihood sequence estimation, the Viterbi algorithm is well known. By summing constants uniquely determined by matched filters and communication channels (as defined by the second and third right terms of Equation 8b, page 18, J. F. Hayes, "The Viterbi Algorithm Applied to Digital Data Transmission", IEEE Communication Society, 1975, No. 13, pages 15-20), a branch metric of received symbol sequences is determined and fed into a soft-decision Viterbi decoder.
However, prior art systems are still not satisfactory if the branch metric is severely affected by channel noise and intersymbol interference. In addition, if variabilities exist in signal to noise ratio between signals received by different diversity antennas during a deep fade, all such signals will be treated alike and an error is likely to result in maximum likelihood sequence estimation.